In [1]:
import plotly.express as px
import seaborn as sb
sb.set(style = "white")
import plotly.graph_objects as gpx
import plotly.io as pio
import kaleido
In [2]:
df = px.data.iris()
df
Out[2]:
sepal_length sepal_width petal_length petal_width species species_id
0 5.1 3.5 1.4 0.2 setosa 1
1 4.9 3.0 1.4 0.2 setosa 1
2 4.7 3.2 1.3 0.2 setosa 1
3 4.6 3.1 1.5 0.2 setosa 1
4 5.0 3.6 1.4 0.2 setosa 1
... ... ... ... ... ... ...
145 6.7 3.0 5.2 2.3 virginica 3
146 6.3 2.5 5.0 1.9 virginica 3
147 6.5 3.0 5.2 2.0 virginica 3
148 6.2 3.4 5.4 2.3 virginica 3
149 5.9 3.0 5.1 1.8 virginica 3

150 rows × 6 columns

LineCharts
In [3]:
fig = px.line(df, y = "sepal_width")
# pio.write_image(fig, 'output_graph.png')
pio.write_html(fig, 'output_file.html')
fig
In [4]:
fig = px.line(df, y = "sepal_width", line_dash="species", color="species")
pio.write_html(fig, 'output_file.html')
fig

Bar Chart
In [5]:
dfA = px.data.tips()
dfA
Out[5]:
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
... ... ... ... ... ... ... ...
239 29.03 5.92 Male No Sat Dinner 3
240 27.18 2.00 Female Yes Sat Dinner 2
241 22.67 2.00 Male Yes Sat Dinner 2
242 17.82 1.75 Male No Sat Dinner 2
243 18.78 3.00 Female No Thur Dinner 2

244 rows × 7 columns

In [6]:
fig = px.bar(dfA, x = "day", y = "total_bill")
pio.write_html(fig, 'output_file.html')
fig
In [7]:
fig = px.bar(dfA, x = 'day', y = 'total_bill', color='sex')
pio.write_html(fig, 'output_file.html')
fig
In [8]:
fig = px.bar(dfA, 'day', 'total_bill', color='sex', facet_row='time')
pio.write_html(fig, 'output_file.html')
fig
In [9]:
fig = px.bar(dfA, 'day', 'total_bill', color='sex',facet_col='sex')
pio.write_html(fig, 'output_file.html')
fig
In [10]:
fig = px.bar(dfA, 'day', 'total_bill', color='sex', facet_row='time',facet_col='sex')
pio.write_html(fig, 'output_file.html')
fig

Scatter Plot
plotly.express.scatter(data_frame=None, x=None, y=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, facet_row=None, facet_col=None, facet_col_wrap=0, opacity=None, title=None, template=None, width=None, height=None, **kwargs)
In [11]:
fig = px.scatter(dfA, x = "total_bill", y = "tip", color="sex")
pio.write_html(fig, 'output_file.html')
fig
In [12]:
fig = px.scatter(dfA, x = "total_bill", y = "tip", color="sex", facet_col="sex")
pio.write_html(fig, 'output_file.html')
fig
In [13]:
fig = px.scatter(dfA, x = "total_bill", y = "tip", color="sex",facet_row="time", facet_col="sex")
pio.write_html(fig, 'output_file.html')
fig
In [14]:
fig = px.scatter(dfA, x = "total_bill", y = "tip", color="time", symbol="sex", size="tip")
pio.write_html(fig, 'output_file.html')
fig
In [15]:
fig = px.scatter(dfA, x = "total_bill", y = "tip", color="time", symbol="sex", size="size", 
                 facet_row="day", facet_col="time")
pio.write_html(fig, 'output_file.html')
fig

Histogram
plotly.express.histogram(data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, barnorm=None, histnorm=None, nbins=None, title=None, template=None, width=None, height=None)
In [16]:
fig = px.histogram(dfA, x = "total_bill")
pio.write_html(fig, 'output_file.html')
fig
In [17]:
fig = px.histogram(dfA, "total_bill", color="sex", nbins=50, histnorm="percent", barmode="group")
pio.write_html(fig, 'output_file.html')
fig
#barmode can be ----- overlay, relative or group
In [18]:
px.histogram(dfA, x = "total_bill", y = "sex")
# pio.write_html(fig, 'output_file.html')

Pie Chart
plotly.express.pie(data_frame=None, names=None, values=None, color=None, color_discrete_sequence=None, color_discrete_map={}, hover_name=None, hover_data=None, custom_data=None, labels={}, title=None, template=None, width=None, height=None, opacity=None, hole=None)
In [19]:
px.pie(dfA, names="day")
In [20]:
px.pie(dfA, names="day", values="total_bill")
In [21]:
px.pie(dfA, names="day", values="total_bill", hole=0.5, opacity=0.8, 
       color_discrete_sequence=px.colors.sequential.RdBu)

Box Plot
plotly.express.box(data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, title=None, template=None, width=None, height=None, **kwargs)
In [22]:
px.box(dfA, x = "day", y = "tip")
In [23]:
px.box(dfA, x = "day", y = "tip", color="sex")
In [24]:
px.box(dfA, x = "day", y = "tip", color="sex", facet_row="time", notched=True)
In [25]:
px.box(dfA, x = "day", y = "tip", color="sex", facet_row="time", facet_col="sex",notched=True)

Violin Plots
In [26]:
px.violin(dfA, x = "day", y = "tip")
In [27]:
px.violin(dfA, x="day", y="tip", color="sex", facet_row="time")

3D Scatter Plots
plotly.express.scatter_3d(data_frame=None, x=None, y=None, z=None, color=None, symbol=None, size=None, range_x=None, range_y=None, range_z=None, title=None, template=None, width=None, height=None, **kwargs)
In [28]:
px.scatter_3d(dfA, x = "total_bill", y = "sex", z = "tip")
In [29]:
px.scatter_3d(dfA, x = "total_bill", y = "sex", z = "tip", size = "total_bill", color="day", symbol="time")
In [30]:
plot = gpx.Figure(data = [gpx.Scatter(
    x = dfA['day'],
    y = dfA['tip'],
    mode = 'markers'
)])

plot.update_layout(
    updatemenus = [
        dict( buttons = list([
                dict(
                    args = ["type", "scatter"],
                    label = "scatter plot",
                    method = "restyle"
                ),
                dict(
                    args = ["type", "bar"],
                    label = "bar chart",
                    method = "restyle"
                )
            ]),
            direction = "down",
        ),
    ]
)